Skip to main content
SpringerLink
Log in

Investigation of the milling stability based on modified variable cutting force coefficients

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The cutting force signal distortion is caused by the dynamic characteristics of cutting force testing system. In order to handle this issue, we propose two improvements in the traditional inverse filtering technology. Firstly, we use three-spline interpolation method instead of the curve fitting method to fit the frequency response function of the test system which basically improves the accuracy of fitting. Secondly, the low-pass filter is added before the inverse filter to eliminate the influence of the high-frequency noise signal on the cutting force signal. We choose the cavity-free surface of outer covering parts of mold of automobile as research objects. The inverse filter dynamic compensation technology has been used to remove the influence of the dynamic characteristics of the test system and the high-frequency noise on the cutting force signal. The effectiveness of the proposed method is verified by relative milling experiments. Based on the experimentally measured forces after dynamic compensation, the modified cutting force coefficients are obtained using the average milling force method. The variation law of the cutting force coefficients with the axial depth, the radial width, and the feed rate is examined. Based on the modified variable cutting force coefficients, the 3D stability of the ball end milling cutter surface has been obtained using full-discretization approach. Combining the results from the cutting experiment and the nonlinear method, the stability prediction based on the modified variable cutting force coefficient can improve the prediction accuracy. The results provide theoretical support for the optimization of the machining process of the cavity-free surface of outer covering parts of mold of automobile.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Wu S, Yang L, Liu XL, Zheng ML, Li RY (2017) Effects of curvature characteristics of sculptured surface on chatter stability for die milling. Int J Adv Manuf Technol 89(9–12):2649–2662

    Article  Google Scholar 

  2. Yue CX, Gao HN, Liu XL (2017) Research on the stability of the machining process based on the dynamic cutting force coefficient. Chin J Mech Eng 53(17):193–201

    Article  Google Scholar 

  3. Song Q, Ai X, Tang W (2011) Prediction of simultaneous dynamic stability limit of time-variable parameters system in thin-walled workpiece high-speed milling processes. Int J Adv Manuf Technol 55(9):883–889

    Article  Google Scholar 

  4. Wan M, Zhang WH, Qin GH (2008) Strategies for error prediction and error control in peripheral milling of thin-walled workpiece. Int J Mach Tools Manuf 48(12):1366–1374

    Article  Google Scholar 

  5. Li H, Li Y, Mou W (2017) Sculptured surface-oriented machining error synthesis modeling for five-axis machine tool accuracy design optimization. Int J Adv Manuf Technol 89(9–12):3285–3298

    Article  Google Scholar 

  6. Budak E, Altintas Y, Armarego EJA (1996) Prediction of milling force coefficients from orthogonal cutting data. J Manuf Sci Eng 118(2):216–224

    Article  Google Scholar 

  7. Wang JJJ, Zheng CM (2002) Identification of shearing and ploughing cutting constants from average forces in ball-end milling. Int J Mach Tools Manuf 42(6):695–705

    Article  MathSciNet  Google Scholar 

  8. Gonzalo O, Beristain J, Jauregi H (2010) A method for the identification of the specific force coefficients for mechanistic milling simulation. Int J Mach Tools Manuf 50(9):765–774

    Article  Google Scholar 

  9. Altintas Y, Ber AA (2001) Manufacturing automation: metal cutting mechanics, machine tool vibrations, and CNC design. Appl Mech Rev 54(2):84

    Article  Google Scholar 

  10. Yao ZQ, Liang XG, Luo L (2013) A chatter free calibration method for determining cutter runout and cutting force coefficients in ball-end milling. J Mater Process Technol 213(9):1575–1587

    Article  Google Scholar 

  11. Lee P, Altintas Y (1996) Prediction of ball-end milling forces from orthogonal cutting data. Int J Mach Tools Manuf 36(9):1059–1072

    Article  Google Scholar 

  12. Wan M, Ma YC, Feng J, Zhang WH (2016) Study of static and dynamic ploughing mechanisms by establishing generalized model with static milling forces. Int J Mech Sci 114:120–131

    Article  Google Scholar 

  13. Wan M, Feng J, Ma YC, Zhang WH (2017) Identification of milling process damping using operational modal analysis. Int J Mach Tools Manuf 122:120–131

    Article  Google Scholar 

  14. Magnevall M, Lundblad M, Ahlin K (2012) High frequency measurements of cutting forces in milling by inverse filtering. Mach Sci Technol 16(4):487–500

    Article  Google Scholar 

  15. Tlusty J, Jang DY, Tarng YS (1987) Measurements of milling force over a wide frequency range. In Proceedings of the 15th NAMRC, Lehigh University, Bethlehem 273–280

  16. Lapujoulade F (1997) Measuring of cutting forces during fast transient periods. 1st French and German Conference on High Speed Machining, Metz, France 372–376

  17. Castro LR, Vieville P, Lipinski P (2006) Correction of dynamic effects on force measurements made with piezoelectric dynamometers. Int J Mach Tools Manuf 46(14):1707–1715

    Article  Google Scholar 

  18. Park SS, Altintas Y (2004) Dynamic compensation of spindle integrated force sensors with Kalman filter. J Dyn Sys-t Asme 126(3):443–452

    Article  Google Scholar 

  19. Albrecht A, Park SS, Altintas Y (2005) High frequency bandwidth cutting force measurement in milling using capacitance displacement sensors. Int J Mach Tools Manuf 45(9):993–1008

    Article  Google Scholar 

  20. Chae J, Park SS (2007) High frequency bandwidth measurements of micro cutting forces. Int J Mach Tools Manuf 47(9):1433–1441

    Article  Google Scholar 

  21. Wan M, Yin W, Zhang WH (2017) Improved inverse filter for the correction of distorted measured cutting forces. Int J Mech Sci 120:276–285

    Article  Google Scholar 

  22. Jensen SA, Shin YC, Davies P (1996) Inverse filtering of unwanted system dynamics in cutting force measurement. Am Soci Mech Eng Dyn Syst. AND Control Division (Publication) DSC 58: 167-174

  23. Castro LR, Viéville P, Lipinski P (2006) Correction of dynamic effects on force measurements made with piezoelectric dynamometers. Int J Mach Tools Manuf 46(14):1707–1715

    Article  Google Scholar 

  24. Girardin F, Remond D, Rigal JF (2010) High frequency correction of dynamometer for cutting force observation in milling. J Manuf Sci Eng 132(3):031002–031008

    Article  Google Scholar 

  25. Yue CX, Liu XL, Liang SY (2017) A model for predicting chatter stability considering contact characteristic between milling cutter and workpiece. Int J Adv Manuf Technol 88(5–8):2345–2354

    Article  Google Scholar 

  26. Wan M, Ma YC, Zhang WH, Yang Y (2015) Study on the construction mechanism of stability lobes in milling process with multiple modes. Int J Adv Manuf Technol 79(1–4):589–603

    Article  Google Scholar 

  27. Song Q, Shi J, Liu Z (2017) A time-space discretization method in milling stability prediction of thin-walled component. Int J Adv Manuf Technol 89(9–12):2675–2689

    Article  Google Scholar 

  28. Wan M, Dang XB, Zhang WH, Yang Y (2018) Optimization and improvement of stable processing condition by attaching additional masses for milling of thin-walled workpiece. Mech Syst Signal Process 103:196–215

    Article  Google Scholar 

  29. Liu X, Li R, Wu S (2017) A prediction method of milling chatter stability for complex surface mold. Int J Adv Manuf Technol 89(9–12):2637–2648

    Article  Google Scholar 

  30. Rubeo MA, Schmitz TL (2016) Mechanistic force model coefficients: a comparison of linear regression and nonlinear optimization. Precis Eng 45:311–321

    Article  Google Scholar 

  31. Grossi N, Sallese L, Scippa A (2015) Speed-varying cutting force coefficient identification in milling. Precis Eng 42:321–334

    Article  Google Scholar 

Download references

Acknowledgements

This project is supported by the State Program of National Natural Science Foundation of China (51575147) and the Youth Talent Support Program of Harbin University of Science and Technology (201507).

Author information

Authors and Affiliations

  1. The Key Lab of National and Local United Engineering for “High-Efficiency Cutting & Tools”, Harbin University of Science and Technology, Harbin, 150080, China

    Xianli Liu, Haining Gao, Caixu Yue, Rongyi Li, Nan Jiang & Lin Yang

Authors
  1. Xianli Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Haining Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Caixu Yue
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rongyi Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nan Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Lin Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xianli Liu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, X., Gao, H., Yue, C. et al. Investigation of the milling stability based on modified variable cutting force coefficients. Int J Adv Manuf Technol 96, 2991–3002 (2018). https://doi.org/10.1007/s00170-018-1780-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-018-1780-9

Keywords

Search

Navigation